• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.27-32
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• 2003

An efficient soft-decision decoding algorithm for binary block codes it proposed. The proposed soft-decision decoding algorithm is implemented by a series of hard-decision decoding process. By the hard-decision decoding result, the candidate codewords are efficiently searched for A new decoding method, which prevents the missing of the candidate codeword, is proposed. Also, the method fir reducing complexity is developed. This method removes the practical complexity increase caused by the improved algorithm. There facts are confirmed by the simulation results for binary (63, 36) BCH code.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.430-435
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• 2018

In this paper, an improved decoding scheme for low-complexity parity-check(LCPC) code with small code length is proposed. The LCPC code is less complex than the turbo code or low density parity check(LDPC) code and requires less memory, making it suitable for communication between internet-of-things(IoT) devices. The IoT devices are required to have low complexity due to limited energy and have a low end-to-end delay time. In addition, since the packet length to be transmitted is small and the signal processing capability of the IoT terminal is small, the LCPC coding system should be as simple as possible. The LCPC code can correct all single errors and correct some of the two errors. In this paper, the proposed decoding scheme improves the bit error rate(BER) performance without increasing the complexity by correcting both errors using the soft value of the modulator output stage. As a result of the simulation using the proposed decoding scheme, the code gain of about 1.1 [dB] was obtained at the bit error rate of $10^{-5}$ compared with the existing decoding method.

• ETRI Journal
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• v.31 no.3
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• pp.336-338
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• 2009

This letter proposes a complexity reduction method to speed up the noiseless decoding of a bit-sliced arithmetic coding (BSAC) decoder. This scheme fully utilizes the group of consecutive arithmetic-coded symbols known as the decoding band and the significance tree structure sorted in order of significance at every decoding band. With the same audio quality, the proposed method reduces the number of calculations that are performed during the noiseless decoding in BSAC to about 22% of the amount of calculations with the conventional full-search method.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.435-449
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• 1997

In this paper, a new metric, universal metric, is Proposed for sequential decoding of convolutional decoding. The complexity of Fano metric for Fano's sequential decoding algorithm is compared with that of the proposed universal metric. Since the Fano metric assumes that it has previous knowledge of channel transition probability, the complexity of Fano metric increases as the assumed channel error probability does not coincide with the true channel error probability. However, the universal metric dose not require the previous knowledge of the channel transition probability since it is estimated on a branch by branch basis. It is shown that the complexity of universal metric is much less than that of the Fano metric for bursty noisy channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1419-1426
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• 1997

A new SCEE(Syndrome Check Error Estimation) decoding method for convolutional code and concatenated SCEE/RS (Reed-Solomon) conding scheme are proposed. First, we describe the operation of the decoding steps in the proposed algorithm. Then deterministic values on the decoding operation are drived when some combination of predecoder-reencoder is used. Computer simulation results show that the compuatational complexity of the proposed SCEE decoder is significantly reduced compared to that of conventional Viterbi-decoder without degratation of the $P_{e}$ performance. Also, the concatenated SCEE/RS decoder has almost the same complexity of a RS decoder and its coding gain is higher than that of soft decision Viterbi or RS decoder respectively.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• ETRI Journal
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• v.36 no.4
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• pp.564-571
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• 2014

Sphere decoding (SD) for multiple-input and multiple-output systems is a well-recognized approach for achieving near-maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM-MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal-to-noise ratio regime. To demonstrate the potential of our method, we compare the results with another well-known method - namely, probabilistic tree pruning SD.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.411-421
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• 2013

Digital fountain codes are record-breaking codes for erasure channels. They have many potential applications in both wired and wireless communications. Most existing digital fountain codes operate over binary fields using an iterative belief-propagation (BP) decoding algorithm. In this paper, we propose a new iterative decoding algorithm for both binary and nonbinary fields. The basic form of our proposed algorithm considers both degree-1 and degree-2 check nodes (instead of only degree-1 check nodes as in the original BP decoding scheme), and has linear complexity. Extensive simulation demonstrates that it outperforms the original BP decoding scheme, especially for a small number of source packets. The enhanced form of the proposed algorithm combines the basic form of the algorithm and a guess-based algorithm to further improve the decoding performance. Simulation results demonstrate that it can provide better decoding performance than the guess-based algorithm with fewer guesses, and can achieve decoding performance close to that of the maximum likelihood decoder at a much lower decoding complexity. Last, we show that our nonbinary scheme has the potential to outperform the binary scheme when choosing suitable degree distributions, and furthermore it is insensitive to the size of the Galois field.

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.742-748
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• 2010

Instead of using sphere decoding, list sphere decoding (LSD) has been introduced to increase the reliability of log-likelihood ratio (LLR) in recent soft decoding schemes employing iterative detection and decoding (IDD). Although LSD provides improved performance, it does not obtain complexity gain due to signal-to-noise ratio (SNR) increment as it detects large number of lattice points. Especially, its inefficient scenario arises when it has to search for lattice points which have small affect for obtaining LLR with high reliability. In this paper, we study an efficient algorithm to remove such lattice points, which results in complexity reduction based on radius optimization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.180-187
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• 2002

The decoding method using covering polynomials is an extended form of error-trapping decoding, and is a simple and effective means to implement decoders for cyclic codes. Covering polynomials can be used for soft-decision decoding as well as for decoding beyond the bounded distance of the code. The implementation complexity is proportional to the number of covering polynomials employed. In this paper, the soft-decision decoding procedure using covering polynomials is described, and the procedure is applied to the [23,12] Golay code. A new set of covering polynomials is derived for the procedure, which is presented as a generalized closed-form solution. The set can be efficiently utilized for decoding a class of cyclic codes including the Golay code. Computer simulation of the described procedure is performed to show the trade-offs between the decoder performance and complexity. It is demonstrated that soft-decision decoding of the Golay code using the derived set of covering polynomials has less than 0.2dB deviation from the optimal performance of maximum-likelihood decoding, with a reduced complexity when compared to the Chase Algorithm 2 combined with hard-decision decoding that has nearly identical performance.